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Introduction: What is Artificial Intelligence? Foundations of AI,
history, the state of art AI today.
Intelligent Agents: agents and environment, good behavior, nature of
environment, the structure of agents.
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II Solving Problems by Searching: Problem solving agents, examples
problems, searching for solutions, uninformed search, informed search
strategies, heuristic functions.
Beyond Classical Search: local search algorithms, searching with
non-deterministic action, searching with partial observations, online
search agents and unknown environments.
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III Adversarial Search: Games, optimal decisions in games, alpha-beta
pruning, stochastic games, partially observable games, state-of-the-are
game programs.
Logical Agents: Knowledge base agents, The Wumpus world, logic,
propositional logic, propositional theorem proving, effective
propositional model checking, agents based on propositional logic.
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IV First Order Logic: Syntax and semantics, using First Order Logic,
Knowledge engineering in First Order Logic.
Inference in First Order Logic: propositional vs. First Order,
unification and lifting, forward and backward chaining, resolution.
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V Planning: Definition of Classical Planning,Algorithms for planning
as state space search, planning graphs, other classical planning
approaches, analysis of planning approaches, Time, Schedules and
resources, hierarchical planning, Planning and Acting in Nondeterministic
Domains, multiagent planning,
Knowledge Representation: Categories and Objects, events, mental
events and objects, reasoning systems for categories, reasoning with
default information, Internet shopping world